Signify Premium Insight: RadNet Hopes to Make AI Pay

One of the barriers slowing the adoption of medical imaging AI is the lack of reimbursement, with providers only able to claim for the use of a handful of tools from payers. Without providers being able to claim , they are typically being forced to pay for their use out of their own pockets. For providers to do this there needs to be a wealth of evidence that the solution is not only going to improve care for patients, but also offer value for providers, evidence that is, in many cases at least, lacking. The process of payer assessment of AI tools is also generally slow and a moving target even once a tool is reimbursable, as the value reimbursed can vary in the future. Thus early pre-emptive adoption of AI tools ahead of reimbursement is fraught with risk.

RadNet, however, is at the vanguard of several other vendors which have found another way. The outpatient imaging provider is, in this instance, also classified as a vendor through its acquisitions of AI ISVs, including DeepHealth, Aidence, and Quantib. Instead of waiting for reimbursement, RadNet has decided to charge patients directly. A move which it expects to generate the company up to $18m in AI revenues this year